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Shell + Skills + Compaction: Tips for long-running agents that do real work

developers.openai.comSaved February 12, 20269 min

Technical Guide

Summary

The blog shows how to build reliable long‑running OpenAI agents by combining Skills, hosted Shell containers, and server‑side context compaction. It gives concrete patterns for skill schema design, container reuse, network allowlists, and artifact handling.

Highlights

Skills provide reusable, versioned instruction bundles that can be loaded on demand.
Hosted Shell runs code in secure, warm containers for continuity across calls.
Server‑side compaction automatically compresses history to stay under token limits.
Write precise skill schemas with negative examples and store prompt templates inside skills.
Reuse the same container, lock down network allowlists, and use /mnt/data for persisted artifacts.

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Preview of Shell + Skills + Compaction: Tips for long-running agents that do real work

Context

Audience

Developers building production‑grade AI agents and engineers interested in agentic workflow design

DomainGenerative AI Agent Development

Formatblog article with code snippets

Accessfree online

Topics

Context Compaction Shell Tool AI Agents Agentic Workflows OpenAI Skills

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OpenAI Responses API docsLangChain agentsLLMOps patternsPrompt engineeringContainer security

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Shell + Skills + Compaction: Tips for long-running agents that do real work

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Highlights

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Shell + Skills + Compaction: Tips for long-running agents that do real work

Summary

Highlights

Context

Topics

Related

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Shell + Skills + Compaction: Tips for long-running agents that do real work

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Shell + Skills + Compaction: Tips for long-running agents that do real work

Summary

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Discover Similar Content

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